Assistant Professor @NYUGSOM_PMED @nyugrossman see also: https://xitter.cf/t.co/cXQ2PgsuFR
New York, NY
Joined May 2017
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Igor Dolgalev retweeted
scBaseCamp was built by directly mining all publicly accessible 10X Genomics scRNAseq data from the Sequence Read Archive (SRA)
With over 230M cells drawn from 21 species, 72 tissues, scBaseCamp is significantly larger and more diverse than existing single-cell data repositories
Igor Dolgalev retweeted
The wait is over!! We are thrilled to announce that we have chosen Spatial Proteomics as 2024’s Method of the Year! 🥳
For more on Spatial Proteomics and a road map to this special issue, please see this month’s Editorial or read on in this thread.
nature.com/articles/s41592-0…
Igor Dolgalev retweeted
This is great! @NIAIDNews have launched a collection of public domain illustrations (currently 550 individual icons) bioart.niaid.nih.gov/
Igor Dolgalev retweeted
🗨️ WANNA TALK TO YOUR CELLS? Try out CellWhisperer – our new multimodal AI that turns single-cell RNA-seq analysis into a conversation. No coding needed, just chat in plain English. Short walkthrough below. Web app & bioRxiv preprint linked in the thread. Let's dive in! (1/9)
Igor Dolgalev retweeted
Here we go…repurposing spatial imaging techs to achieve ultra-low to ultra-high, multiplexing, nuclei, cells, single (RNA or Protein), multimodal (RNA and Protein), super cheap! NO SEQUENCING!
@10xGenomics @nanostringtech @AkoyaBio @bruker
STAMP: Single-Cell Transcriptomics Analysis and Multimodal Profiling through Imaging | bioRxiv
@DrJasPlummer @hoheyn @pascual_reguant @eliseinsing @cnag_eu @ACEpigenetics @StJudeResearch biorxiv.org/content/10.1101/…
Igor Dolgalev retweeted
There's a lot of excitement about foundation models and their ability to learn biology 🧬💻
But current tools for perturbation prediction perform worse than simple linear models! We need more careful benchmarking to make progress.
biorxiv.org/content/10.1101/…
ALT Beeswarm plot of the double perturbation predictions. The Additive model outperforms GEARS, scGPT, and scFoundation by a large margin
ALT Line plot of the accuracy of the predictions that are most different from the additive model. The No Change model outperforms GEARS, scGPT, and scFoundation.
ALT Beeswarm plot of the single perturbation predictions. The linear model perform as good as GEARS, scGPT, and scFoundation.
Igor Dolgalev retweeted
Are you missing cells and cell types in your single-cell multiome experiments @10xGenomics? Check out EmptyDropsMultiome @MarioniLab
Igor Dolgalev retweeted
$ILMN - Illumina buys Fluent Biosciences to accelerate single-cell analysis seekingalpha.com/news/412309…
Igor Dolgalev retweeted
Systematic comparison of sequencing-based spatial transcriptomic methods in @naturemethods
In summary:
“- Stereo-seq, Slide-tag, Visium shows the better capture efficiency with raw sequencing depth
- Slide-seq V2, Visium (probe), DynaSpatial gives the better capture efficiency with normalized sequencing depth.”
nature.com/articles/s41592-0…
Igor Dolgalev retweeted
I'm happy to share that out paper on Phantasus, a web-application for visual and interactive gene expression analysis, got out in @eLife elifesciences.org/articles/8… Here, I'm using it to analyze a random GEO dataset, including basic QC to filter outliers, in under 100 seconds! 1/n
Igor Dolgalev retweeted
🌎👵⚤ Excited to share
Multi-organ map of the human immune system across age, sex and ethnicity
From 29M cells and 12K samples from @humancellatlas, tissue-specific #Ageing programs, sexual
#dimorphism, #Ethnical diversity in #Immunotherapy targets
biorxiv.org/content/10.1101/…
Igor Dolgalev retweeted
@10xGenomics released new single cell GEM-X assays in March, and we were quick to try it out. FHIL benchmarked 5’ GEM-X against 5’ Next GEM v2 chemistry with sorted T-cells from healthy donor PBMCs and targeted the recommended max for each assay, 20k and 10k respectively.(1/8)
Igor Dolgalev retweeted
(1/5) Attention, Cellular Imaging Enthusiasts!
Thrilled to share that our Analysis "The Multi-modality Cell Segmentation Challenge: Towards Universal Solutions" has been published in Nature Methods (@NatureMethods) 🎉🎉🎉
Cell segmentation is a critical component of microscopy image analysis, but existing algorithms are often specialized for particular types of images or demand users to manually set hyper-parameters, posing challenges for biologists without a strong computational background.
To address these issues, we organized an international challenge at NeurIPS 2022 to promote the development of novel cell segmentation methods that excel across a wide array of microscopy images, imaging platforms, and tissue types.
🌐 Homepage: uni-cellseg.github.io/
📄 Paper: nature.com/articles/s41592-0…
🔬Data: neurips22-cellseg.grand-chal…
🏅Competition website: neurips22-cellseg.grand-chal…
👇 👇👇👇
Igor Dolgalev retweeted
Excited to announce our Human Bone Marrow Progenitor Atlas (doi.org/10.1038/s41590-024-0…).
>80 rare stem/progenitor states delineated through multimodal (CITE-Seq) integration w/ prior cell atlas labels (scTriangulate).
Validated by InfinityFlow, sorting & in vitro differentiation.
Igor Dolgalev retweeted
Hot off the press! #singlecell learning on the go. Watch this nine-part miniseries to learn:
🔑 Key considerations for single cell experimental design
📕 Best practice guidance for successful sample preparation
🔎 Single cell analysis workflow
10xgen.com/1AW
Igor Dolgalev retweeted
Gene expression in tumor-adjacent tissue holds significant prognostic insight in predicting lung adenocarcinoma reoccurrence, @NYUGSOM_Path research finds.
Learn more with investigators Dr. Igor Dolgalev (@bioigor) & Dr. Aristotelis Tsirigos (@artsinyc): bit.ly/3SKy97u
Igor Dolgalev retweeted
Fighting unfair multijurisdictional litigation for 3 yrs siphoned precious resources. To protect NanoString, fortify our ability to serve customers, & provide the same fantastic products & services we are announcing a voluntary Chapter 11 restructuring. bit.ly/3SLw2Bp
Igor Dolgalev retweeted
Researchers Caught in Crossfire as High-Resolution Spatial Technology Providers Wage Turf War. Frustrations with spatial tissue profiling technologies have prompted researchers from around the world to band together and get everyone on the same page. ow.ly/w63R105eql1